Adaptive Neuro-Fuzzy Self Tuned-PID Controller for Stabilization of Core Power in a Pressurized Water Reactor

Abdelfattah, H.; Kotb, Said A.; Esmail, Mohamed; Mosaad, Mohamed I.

doi:10.31763/ijrcs.v3i1.710

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…The fuzzy logic control system is a control system that utilizes ambiguous reasoning to control operations and infer solutions in the system. It has been widely studied and used in controlling various systems and controllers [96], [97], [98], [99], [100], [101]. In the context of robotic arm motor control, the Mamdani method is commonly used to estimate the ambiguous control input, as shown in Fig.…”

Section: Fuzzy Logic Control Systemmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.

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Section: Fuzzy Logic Control Systemmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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“…They provide functionalities that allow systems to handle transient and steady-state responses. Aside from their simplicity in construction, proportional-integralderivative controllers possess the capability to provide valuable solutions to a variety of practical challenges, as indicated in [3,4]. The PID control variant uses multiple methods to calculate integral and derivative values.…”

Section: Introductionmentioning

confidence: 99%

“…The PID control variant uses multiple methods to calculate integral and derivative values. Furthermore, a self-adjusting PID controller using Adaptive Neuro-Fuzzy (ANF) technology was presented in [4] for the nuclear core reactor application. This article utilizes the adaptive controller approach to enhance the performance characteristics of the Pressurized Water Reactor (PWR).…”

Section: Introductionmentioning

confidence: 99%

Design of a Decentralized PID Controller Using the Relative Gain Array Technique for a Coupled Flotation Process

Tshemese-Mvandaba

2024

IJEETC

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This study focuses on the design of the decentralized Proportional-Integral-Derivative (PID) controller for a coupled flotation system. It emphasizes the difficulties encountered when dealing with interconnected Multiple-Input Multiple-Output (MIMO) systems that cannot be effectively regulated using traditional linear feedback controllers. The significance of this article lies in its examination of how the Relative Gain Array (RGA) can be utilized to mitigate the impact of process connections. With the use of a thoughtful selection of single-loop pairings, the decentralized controller is created following the RGA technique. The decentralized controller that has been developed serves the purpose of reducing the influence caused by process interfaces. A set-point tracking technique, based on Internal Model Controllers (IMCs) is adopted in the design. The system time response and overshoot were also analyzed. The paper proposed a decentralized control mechanism and provided a comprehensive process for applying it to both the system under investigation and different MIMO industrial processes. The performance of the suggested closed-loop system was simulated and confirmed using Matlab/Simulink.

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A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

Shamseldin,

Salah,

Mohamed

et al. 2023

International Journal of Electrical Engineering and Computer Science

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In this research, a new one-axis servomechanism investigation is presented, taking into account parameter fluctuation and system uncertainty. Additionally, a novel method for very effective TID control was created to accurately monitor a chosen profile. A comparative study between the suggested control method and the well-known controllers (PID and Nonlinear PID) is also included. The COVID-19 optimization technique was used to discover the best control parameters. Through the online simulation, the servomechanism system's settings were modified at random within a predetermined range. As nonlinearity resources (friction, backlash, environmental influences), these parameters fluctuate and contribute to system uncertainty. It had been completed and looked at to compare the linear and nonlinear models. The results demonstrate that the suggested controller is capable of tracking the number of operational points with high accuracy, a short rising time, and little overrun.

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Adaptive Neuro-Fuzzy Self Tuned-PID Controller for Stabilization of Core Power in a Pressurized Water Reactor

Cited by 3 publications

References 16 publications

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Design of a Decentralized PID Controller Using the Relative Gain Array Technique for a Coupled Flotation Process

A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model

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